The International Wage Flexibility Project

The International Wage Flexibility Project

Labor Markets and Inflation: The International Wage Flexibility Project Presentation at National Bank of Belgium Conference on Wage and Price Rigidities in an Open Economy 13 October, 2006 What is the IWFP? 13 Country study of wage inflation Sponsored by the ECB and directed by Erica Groshen (NY Fed.) and me using micro data on individual and occupational wages analyzed by teams in each country familiar with the data to be used meta-analysis of country level results by team including directors plus Lorenz Goette, Steinar Holden, Julian Messina, Mark E. Schweitzer, Jarkko Turunen, and Melanie E. Ward broader than just analyzing wage rigidity (sand and grease), but that is the part that Im going to talk about today Where to Find Full Paper Results: http://brookings.edu/es/research/projects/iwfp_jep.pdf Methodology: http://brookings.edu/es/research/projects/200509_iwfp.pdf Or navigate to brookings.edu then go to list of scholars then go to my page then look under current projects for 13 country study of wage rigidity and click through to that page all the papers for this project are linked to that page Country Teams Austria Belgium Denmark

Finland France Germany Italy Norway Portugal Sweden Switzerland United Kingdom United States Disclaimer! Opinions expressed in this presentation are mine and mine alone. They should not be attributed to any other individuals in the IWFP, their employers, or associates, nor should they be attributed to the organizations sponsoring the IWFP. My Motivation Today many central banks have chosen to explicitly target inflation (and the ones that dont often do it implicitly). Many of these targets are very low (2% or less). In 1996 article with Akerlof and Perry (ADP) we showed that low inflation in the presence of downward nominal rigidity could lead to substantial unemployment in the long run. Is overly low inflation causing considerable unemployment (particularly in Europe where unemployment rates have been stubbornly high)? Although ADP model fits well for US and Canada, it fits very poorly for Britain and continental European countries. Is real rigidity a confounding problem that makes ADP model inappropriate? Motivation (Continued) Most previous (pre IWFP) studies of European wage rigidity use macro data to determine extent (and concept of

rigidity measured is slow adjustment to economic circumstances rather than downward rigidity) Early exceptions include Smith (2000) and Nickell and Quintini (2001) who both analyze British micro wage data and find much less evidence of DNWR than in US data Biscourp et al. (2004) find mixed results for France Knoppik and Thomas Beissinger (2003) find substantial DNWR in Germany Fehr and Gotte (2004) find substantial DNWR in Switzerland Is there really substantial variation across countries or do differences reflect methodological differences? How To Measure Rigidity? Initially we were unsure about how to get at presence of different types of rigidity. I was mainly interested in looking at the extent of DNWR across countries using consistent methodology. At first meeting some very interesting results emerged examining wage change histograms. What We Are Going to See Histograms of wage percentage wage changes We are looking only at job stayers In some cases we are looking at reported hourly wages In other cases a measure of income divided by hours of work Some are from surveys, some from social security data, some from other types of administrative records Figure 1: Alternative Wage Change Distributions .1 .05 0 0 .05 .1 .15

Finland 1988 .15 United States 1987 -15 -10 -5 0 5 10 15 20 25 -15 -10 -5 5 10 15 20 25 15 20 25 .1 .05

0 0 .05 .1 .15 Ireland 1996 .15 United Kingdom 1984 0 -15 -10 -5 0 5 10 15 20 25 -15 -10 -5 0 Black lines indicate contemporaneous and prior year's inflation rates Red-Normal, Green-Weibull, Blue Bars-Data, Yellow-Zero Spike

5 10 Can we use wage change histograms to diagnose the nature and extent of wage rigidity? Wage Change Distribution (For workers with same wage facing same minimum wage) Observatuions Swept Down to Zero by Menu Costs Observations Swept Up to Rate of Price Inflation By Downward Real Wage Rigidity Observations Swept Up to Zero By Downward Nominal Wage Rigidity and Menu Costs Frequency No Nominal Wage Change No Real Wage Change 0.26 0.23 0.20 0.17 0.14 0.11 0.08 0.05 0.02 -0.01

-0.04 -0.07 -0.10 -0.13 -0.16 -0.19 -0.22 Change in Log Wage Big Problem is Measurement Error If people make mistakes reporting their wages then we see wage changes where there are none. If we compute wage=income/hours we see wage changes due to overtime, bonuses, or mistakes in reporting hours. If we use SS data we have similar problems since almost no country has data that allow us to accurately identify base wage. All evidence suggests that for most data sets frequency and extent of errors make this a very serious problem (evidence suggests that in many data sets most reported wage cuts are actually errors of these sorts). Correcting for Errors Use information in correlation between years Abowd and Card (1989) suggest that wages have two components: permanent changes transient (one period) changes (which result in negative serial correlation of wage changes) New method identifies transient changes as errors and uses auto-covariance and frequency of sign switching in changes to identify error rate and error variance. This information is used to identify semi-non-parametric estimate of true wage distribution (that is we estimate the histogram of wage changes we would see if there were no errors). How Do We Know Frequency and Severity of Errors?

First crucial assumption is that errors are only important source of covariance in wage changes from one year to next. With that assumption we can identify the frequency of errors, and the variance of those errors when they are made, by looking at the autocovariance of wage changes and the number of people who have sequential large wage changes of opposite signs. We estimate a statistical model of the wage change distribution and the error process using method of moments. Validating Primary Assumption Results applying new method to US largely fit with those of other studies (a very high degree or downward nominal rigidity). Finnish and German data has virtually no errors and estimated covariances are tiny and sometimes positive. Portuguese have good and bad data and (as we will see) the correction doesnt change the good data, but makes the bad data look like the good data. Portugese Data Base wage - 1994 Base wage+other labor earnings -1994 0.12 0.12 0.1 0.1 0.08 0.08 0.06 0.06 0.04 0.04 0.02

0.02 0 0 -25 -23 -21 -19 -17 -15 -13 -11 -9 -0.02 -7 -5 -3 -1 1 3 5 7 9 -25 -23 -21 -19 -17 -15 -13 -11 -9 -7 -5 -3 -1 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 -0.02 Base wage+other labor earnings-1992 Base wage-1992 0.15 0.15

0.13 0.13 0.11 0.11 0.09 0.09 0.07 0.07 0.05 0.05 0.03 0.03 0.01 0.01 -25 -0.01 -22 -19 -16 -13 -10 -7 -4 -1 2 5 8

11 14 17 20 23 26 29 32 35 38 41 44 47 50 -25 -0.01 -22 -19 -16 -13 -10 -7 -4 -1

2 5 8 11 14 17 20 23 26 29 32 35 38 41 44 47 50 More Validation Analysis of Gottschalk Data Gottschalk uses regression discontinuity analysis of individual micro data to discriminate between true wage changes and errors in SIPP quarterly data (finds almost no negative wage changes) . We analyzed his data and found that all auto- covariance in wage changes due to errors (validating our identifying assumption). Three Ways to Estimate Three Types of Rigidity

Problem is to generate counterfactual distribution (or notional wage change distribution) with which to compare actual wage change distribution. Three possibilities Assume an ideal form for the notional distribution Assume that the notional distribution is symmetric Assume that the notional distribution has constant shape over time We use the ideal form method (2-sided Weibull) Frequency Figure 6 2-Sided Weibull vs. Actual for US 97 0.18 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 Percentage Wage Change Actual Weibull Figure 7 2-Sided Weibull vs. Actual for UK 1988 0.1 0.06 0.04 0.02 Percentage Wage Change Actual Weibull 0.28 0.25 0.22

0.19 0.16 0.13 0.10 0.07 0.04 0.00 -0.02 -0.05 -0.08 -0.11 -0.14 -0.17 0 -0.20 Frequency 0.08 Ideal Distribution (only method Im going to discuss today) In general, two-sided Weibull fits upper tail of nearly all distributions very well and Gottshalks true wage changes (upper tail) have two-sided Weibull shape. So we will assume that notional wage change distribution is 2-sided Weibull and estimate its parameters along with A fraction r of workers are subject to downward real wage rigidity and if their notional wage change < expected inflation they get expected inflation A fraction n of workers are subject to downward nominal wage rigidity and if their notional wage change <0 they get wage freeze.

A fraction of workers are subject to symmetric nominal rigidity and get no wage change if their notional wage change is within 2% of zero on either side Aside: What Sort of Process Gives Rise to Weibull? Wage increases (above some average level) result from tournament with winners at each level getting an increase of a fixed size and then competing only with winners of first round for a larger increase in next round. Size of increase from winning a round grows exponentially. This is notably different from normal distribution that would result if workers were evaluated on many independent criteria and then given raises depending on how many they satisfied. 0 .2 .4 .6 .8 Real and Nominal Ridigity by Country Real Rigidity Nominal Rigidity International Comparisons Considerable variation across countries in the extent of downward nominal and downward real wage rigidity despite correction for differences in data quality Some tendency for countries to have either DNWR or DRWR but not both (tendency is stronger when we restrict comparison to the 90s) How do our estimates compare to those of others and between different data sources in our own sample? ECHP results with other data sets correlate .53 for both real and nominal rigidity Wouldnt expect perfect correlation since time periods dont overlap and we do see some changes over time Country averages for nominal rigidity correlate .55 with simple

measures constructed from uncorrected data Country averages for real rigidity correlate .25 with simple measure used in JEP paper constructed from uncorrected data .6 Comparing DNWR fromdifferent datasets Country Estimates. 1990s .2 .3 .4 .5 Portugal Italy France Austria UK Denmark Finland .1 Germany 0 .2 .4 ECHP Estimates .6 .8 Holden and Wulfsberg r=.45(.08) 1 Italy Portugal

.8 .8 1 Knoppik and Beissinger r=.74(.09) Finland Belgium Austria PortugalGreece Denmark Sweden Austria Netherlands Greece .2 UK Ireland Switzerland Finland France 0 0 .2 .4 .6 IWFP n ECHP only Denmark Germany Belgium 0 .2 Germany

France Ireland UK Norway HW DNWR .4 .6 KB DNWR .4 .6 Italy .8 0 .2 .4 IWFP n Source: HW (2005) FWCP from Table B1, page 38; KB (2005) Table 4, page 29 and IWFP. .6 .8 What is Correlated with Downward Nominal Rigidity? 1.0 1.0 0.9 NL 0.8 0.7 NL 0.8 IT

US 0.7 PT 0.6 n GR 0.9 GR US 0.5 n SZ 0.4 AT DK 0.5 SZ 0.4 FR SE 0.3 FI UK IE 0.1

BE FR DK FI UK 0.2 NO NO IE BE 0.1 DE 0.0 DE 0.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 0.0

0.5 1.0 1.5 Aggregate EPL 2.0 2.5 3.0 3.5 Corporatism 1.0 1.0 0.9 0.9 GR NL 0.8 0.7 US PT 0.7 IT GR NL 0.8 IT US PT

0.6 0.6 0.5 n SE SZ 0.4 FR DK AT 0.3 UK 0.2 IE 0.1 NO FI 0.4 FR AT 0.3 DK SZ SE FI UK IE

0.1 BE DE 0.5 0.2 0.0 NO BE DE 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0.0 0.2 0.4 Union Density 0.6

0.8 1.0 1.2 Wage Indexation 1.0 1.0 0.9 GR 0.8 0.7 US 0.9 NL NL 0.8 0.7 IT PT 0.6 n AT SE 0.3 0.2 n

IT PT 0.6 IT GR US PT 0.6 n 0.5 SZ 0.4 SE DK AT FR 0.3 0.5 0.4 0.3 FI UK 0.2 IE 0.1 NO 0.2

BE SE SZ AT DK FI UK IENO BE 0.1 DE 0.0 FR DE 0.0 0.0 20.0 40.0 60.0 Bargaining Coverage 80.0 100.0 0.0 10.0 20.0 30.0

40.0 50.0 Minimum Wage / Average Wage 60.0 70.0 What is Correlated with Downward Real Wage Rigidity? 0.6 0.6 SE FI 0.5 0.4 r PT 0.3 AT UK r NO 0.2 DE AT UK US 1.5 2.0

IT GR 0.0 2.5 3.0 3.5 4.0 0.0 0.5 1.0 1.5 Aggregate EPL FR FI FR 0.5 FI 0.4 BE IE PT 0.3 UK SZ 0.2 r AT

GR 0.0 0.0 0.1 0.2 0.3 0.0 0.4 0.5 BE NO DE DK US NL 0.1 DK NL 0.3 0.6 0.7 0.8 0.9 0.0 SZ IT GR 0.2

0.4 Union Density 0.6 0.8 1.0 1.2 Wage Indexation 0.6 0.6 SE 0.5 SE FI 0.5 FR 0.4 PT 0.3 UK 0.2 DK 0.1 US GR 0.0 BE

IE AT NO SZ FR FI 0.4 BE IE r 3.5 PT AT 0.2 IT US 3.0 SE UK NO DE 0.1 2.5 0.6

SE 0.4 r 2.0 NL Corporatism 0.6 IE DE DK US GR NL 0.0 0.5 NO 0.1 IT DK 1.0 IE PT 0.3 SZ 0.1

0.5 BE 0.2 SZ 0.0 FR 0.4 BE IE FI SE 0.5 FR r 0.2 DE 0.1 IT PT 0.3 AT UK NO SZ DE DK IT

US NL NL GR 0.0 0.0 20.0 40.0 60.0 Bargaining Coverage 80.0 100.0 0.0 10.0 20.0 30.0 40.0 50.0 Minimum Wage / Average Wage 60.0 70.0 What is Correlated with Rigidity? Nothing consistently statistically significant at conventional levels. Union membership and bargaining coverage variables statistically significant at .1 level (we are getting better results now

using time series variation). Notable case is US where real rigidity was notable in 1970s but disappears in the 1980s after the breakdown of pattern bargaining. Does Rigidity Affect Unemployment? According to Akerlof, Dickens and Perry 1996 a 1 percent increase in in nominal wages due to rigidity should create somewhere between a 1 and 5 percentage point increase in unemployment We compute estimates of the impact of each type of rigidity on wages and estimate a series of models of the impact of rigidity. Table 3 Effects of Rigidity on Unemployment Dependent Variable/Specification Unemployment Change in Inflation (Phillips Curve) Unemployment Effect (b/a) 1.26 .90 2.99 2.90 Standard Error (.35) (.32) (1.28) (2.09) .00 .01

.01 .08 no yes no yes p for null hypothesis 0 b/a (one tail test) Controls for year (all contain controls for dataset (country)) Conclusions on Unemployment Unemployment effects generally statistically significant. Cant reject the hypothesis that unemployment effects are in the range predicted by ADP model. Cant reject the hypothesis that effects of real and nominal rigidity are equal (as theory predicts). (Tentative) Policy Implications Most Euro-zone countries characterized by downward real wage rigidity rather than downward nominal wage rigidity. Benefits of increased inflation may not be so great in those countries compared to US and Canada (recent nominal wage cuts in Germany are example of how corporatist countries can overcome nominal wage rigidity). Several Euro-zone countries have substantial downward nominal wage rigidity so allowing inflation to move to bottom end of ECB target zone could be very costly. Should this happen these countries might be better off if they left EMU. Though gains would be minor given ECB policy to date. More Policy Conclusions No evident effect of EMU on rigidity in these data (though most data dont go back far

enough to tell if there are effects of Maastricht treaty). No Evidence that persistent low inflation reduces the incidence of downward nominal wage rigidity. Thus no evidence that institutions adapt to low inflation. For US new method confirms results of previous studies significant DNWR. New finding is that there is no evidence of DRWR by 1990s. Thus Fed should avoid very low inflation.

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